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应用科学学报 ›› 2004, Vol. 22 ›› Issue (3): 283-286.

• 论文 • 上一篇    下一篇

具有区间数的粗糙神经网络故障认定方法

何亚群1,2, 胡寿松1, 侯霞1   

  1. 1 南京航空航天大学自动化学院 江苏南京 210016;
    2 空军后勤学院三系 江苏徐州 221002
  • 收稿日期:2003-06-26 修回日期:2003-09-19 出版日期:2004-09-30 发布日期:2004-09-30
  • 作者简介:何亚群(1962-),女,浙江海宁人,博士生;胡寿松(1937-),男,浙江慈溪人,教授,博导.
  • 基金资助:
    国家自然科学基金重点项目(60234010);国防基础科研项目;航空科学基金资助项目(02E52025)

A Fault Verification Method of the Rough Neural Network with Interval Numbers

HE Ya-qun1,2, HU Shou-song1, HOU Xia1   

  1. 1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    2. Third Department, Air Force logistics College, Xuzhou 221002, China
  • Received:2003-06-26 Revised:2003-09-19 Online:2004-09-30 Published:2004-09-30

PDF

83

被引次数

16

摘要： 针对具有区间数的信息系统,提出用粗糙神经网络求解其问题的方法.给出了粗糙神经网络的拓朴结构和学习算法以及粗糙神经网络的逼近定理.最后以歼击机的操纵面故障认定为例,构造了歼击机故障认定的粗糙神经网络,并通过仿真说明了方法的可行性和有效性.

关键词: 粗糙集, 粗糙神经网络, 故障认定, 区间数

Abstract: A rough neural network method is proposed to solve the problems in an information system with interval numbers. The topologic structure and learning algorithm of the rough neural network are given, and the approximation theorem of the rough neural network is presented. Finally, to prove the feasibility of the method the rough neural network for fault verification of a fighter plane is constructed, and the simulation results show that the method is feasible and efficient.

Key words: interval numbers, fault verification, rough sets, rough neural network

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